7 papers
Hybrid Cones: Set Representation with Sharp Unions of Minimal Overhead for Nonlinear and Switched Linear Systems
Daniel Silvestre
Reachability analysis and set-based estimation for nonlinear systems require set representations capable of capturing nonconvex geometry. Hybrid Zonotopes (HZs) have recently gaine…
Certifiable Explicit Model Predictive Control for Spacecraft Rendezvous under Bounded Disturbances
Diogo Silva, Daniel Silvestre
Two properties of optimization-based controllers such as model predictive control (MPC) limit their use in space flight. The online computing time varies and can exceed the samplin…
CBF-based Probabilistic Safe Navigation under Unknown Nonlinear Obstacle Dynamics
Jiwon Lee, Hugo Matias, Daniel Silvestre +1
Safe navigation for an ego vehicle in uncertain environments characterized by dynamic obstacles with unknown nonlinear dynamics is a challenging problem of significant practical in…
Fault-Tolerant MPC Control for Trajectory Tracking
David Laranjinho, Daniel Silvestre
An MPC controller uses a model of the dynamical system to plan an optimal control strategy for a finite horizon, which makes its performance intrinsically tied to the quality of th…
Safe Navigation under Uncertain Obstacle Dynamics using Control Barrier Functions and Constrained Convex Generators
Hugo Matias, Daniel Silvestre
This paper presents a sampled-data framework for the safe navigation of controlled agents in environments cluttered with obstacles governed by uncertain linear dynamics. Collision-…
Hybrid Lyapunov and Barrier Function-Based Control with Stabilization Guarantees
Hugo Matias, Daniel Silvestre
Control Lyapunov Functions (CLFs) and Control Barrier Functions (CBFs) can be combined, typically by means of Quadratic Programs (QPs), to design controllers that achieve performan…
Model-Predictive Trajectory Generation for Aerial Search and Coverage
Hugo Matias, Daniel Silvestre
This paper introduces a trajectory planning algorithm for search and coverage missions with an Unmanned Aerial Vehicle (UAV) based on an uncertainty map that represents prior knowl…